Hey @Aetherus thanks 
I’m far from being an expert, but I’ll give it a try and reply to some of your questions:
- How to save a trained model? Is there any language-agnostic standard format?
There are probably multiple ways to do that.
A simple approach is to dump the weights obtained from the training in a file (see Nx.serialize/2), they should be pretty much portable and language/framework-agnositc, but of course the model implementation must be the same. Basically, you need to keep your model definitions as code around and then you can just load the weights and call the predict function.
Another possible way is to convert the trained model to ONNX format (including the weights). In elixir-nx ecosystem you can use the AxonOnnx library.
- How to load a pre-trained model written in another language?
Also in this case, there are more possibilities depending on the model.
First thing, maybe you can check if this model is already available via Bumblebee, that would be the easiest way.
If not, you can check if it is possible to export the model to onnx format and then you can try to import it in Axon via the aforementioned AxonOnnx.
Worst case scenario, you have only the weights at hand and therefore you need to re-implement the model with Axon, in that case you can check Bumblebee models for inspirations.
I’m sure there are probably other ways.
3 How to do transfer learning?
I don’t have any experience about it.
I think this livebook can be a good entry point for fine-tuning Fine-tuning — Bumblebee v0.7.0
Otherwise, I have seen that Axon exposes APIs to freeze layers which can be useful for transfer learning.
Cheers 
